Datasets:

Modalities:
Audio
Text
Formats:
parquet
Languages:
Wolof
ArXiv:
Libraries:
Datasets
Dask
License:
wolof_tts / README.md
derguene's picture
Update README.md
2991f33 verified
metadata
dataset_info:
  features:
    - name: audio
      dtype:
        audio:
          sampling_rate: 16000
    - name: text
      dtype: string
    - name: gender
      dtype: string
  splits:
    - name: train
      num_bytes: 4274917077.83
      num_examples: 36009
    - name: test
      num_bytes: 475541653.87
      num_examples: 4001
  download_size: 4571561616
  dataset_size: 4750458731.7
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
license: cc-by-4.0
task_categories:
  - text-to-speech
language:
  - wo
pretty_name: woloftts
size_categories:
  - 10K<n<100K

Wolof TTS

Dataset Description

This is a Wolof Text To Speech (TTS) dataset collected by Baamtu Datamation as part of the AI4D African language program. The original dataset is hosted on Zenodo and it contains recordings from two (02) natif Wolof speakers (a male and female voice). Each speaker recored more than 20,000 sentences.

Speaking time:

-- Male: 22h 28mn 41s
-- Female: 18h 47mn 19s

The text dataset comes from news websites, Wikipedia and self curated text.

Citation

You can access the project paper at https://arxiv.org/abs/2104.02516.
If you work on the dataset, please cite the authors below.

@dataset{thierno_ibrahima_diop_2021_4498861,
  author       = {Thierno Ibrahima Diop and
                  Demba AW and
                  Ami jaane and
                  Mamadou Badiane},
  title        = {WOLOF TTS(Text To Speech) Data},
  month        = feb,
  year         = 2021,
  publisher    = {Zenodo},
  version      = 1,
  doi          = {10.5281/zenodo.4498861},
  url          = {https://doi.org/10.5281/zenodo.4498861}
}

This dataset was made available on HuggingFace through GalsenAI's mission to strengthen Senegal's AI ecosystem. It was cleaned and structured by Derguene Mbaye, then uploaded and documented by Alwaly Ndiaye.